Abstract: Software project effort estimation is frequently seen
as complex and expensive for individual software engineers.
Software production is in a crisis. It suffers from excessive costs.
Software production is often out of control. It has been suggested that
software production is out of control because we do not measure.
You cannot control what you cannot measure. During last decade, a
number of researches on cost estimation have been conducted. The
metric-set selection has a vital role in software cost estimation
studies; its importance has been ignored especially in neural network
based studies. In this study we have explored the reasons of those
disappointing results and implemented different neural network
models using augmented new metrics. The results obtained are
compared with previous studies using traditional metrics. To be able
to make comparisons, two types of data have been used. The first
part of the data is taken from the Constructive Cost Model
(COCOMO'81) which is commonly used in previous studies and the
second part is collected according to new metrics in a leading
international company in Turkey. The accuracy of the selected
metrics and the data samples are verified using statistical techniques.
The model presented here is based on Multi-Layer Perceptron
(MLP). Another difficulty associated with the cost estimation studies
is the fact that the data collection requires time and care. To make a
more thorough use of the samples collected, k-fold, cross validation
method is also implemented. It is concluded that, as long as an
accurate and quantifiable set of metrics are defined and measured
correctly, neural networks can be applied in software cost estimation
studies with success
Abstract: ''Cocktail party problem'' is well known as one of the human auditory abilities. We can recognize the specific sound that we want to listen by this ability even if a lot of undesirable sounds or noises are mixed. Blind source separation (BSS) based on independent component analysis (ICA) is one of the methods by which we can separate only a special signal from their mixed signals with simple hypothesis. In this paper, we propose an online approach for blind source separation using the sliding DFT and the time domain independent component analysis. The proposed method can reduce calculation complexity in comparison with conventional methods, and can be applied to parallel processing by using digital signal processors (DSPs) and so on. We evaluate this method and show its availability.
Abstract: The present study was designed to test the influence
of confirmed expectations, perceived usefulness and perceived
competence on e-learning satisfaction among university teachers. A
questionnaire was completed by 125 university teachers from 12
different universities in Norway. We found that 51% of the variance
in university teachers- satisfaction with e-learning could be explained
by the three proposed antecedents. Perceived usefulness seems to be
the most important predictor of teachers- satisfaction with e-learning.
Abstract: Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.
Abstract: This article is dedicated to development of
mathematical models for determining the dynamics of
concentration of hazardous substances in urban turbulent
atmosphere. Development of the mathematical models implied
taking into account the time-space variability of the fields of
meteorological items and such turbulent atmosphere data as vortex
nature, nonlinear nature, dissipativity and diffusivity. Knowing the
turbulent airflow velocity is not assumed when developing the
model. However, a simplified model implies that the turbulent and
molecular diffusion ratio is a piecewise constant function that
changes depending on vertical distance from the earth surface.
Thereby an important assumption of vertical stratification of urban
air due to atmospheric accumulation of hazardous substances
emitted by motor vehicles is introduced into the mathematical
model. The suggested simplified non-linear mathematical model of
determining the sought exhaust concentration at a priori unknown
turbulent flow velocity through non-degenerate transformation is
reduced to the model which is subsequently solved analytically.
Abstract: This paper considers various channels of gammaquantum
generation via an ultra-short high-power laser pulse
interaction with different targets.We analyse the possibilities to create
a pulsed gamma-radiation source using laser triggering of some
nuclear reactions and isomer targets. It is shown that sub-MeV
monochromatic short pulse of gamma-radiation can be obtained with
pulse energy of sub-mJ level from isomer target irradiated by intense
laser pulse. For nuclear reaction channel in light- atom materials, it is
shown that sub-PW laser pulse gives rise to formation about million
gamma-photons of multi-MeV energy.
Abstract: University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.
Abstract: The security of their network remains the priorities of almost all companies. Existing security systems have shown their limit; thus a new type of security systems was born: honeypots. Honeypots are defined as programs or intended servers which have to attract pirates to study theirs behaviours. It is in this context that the leurre.com project of gathering about twenty platforms was born. This article aims to specify a model of honeypots attack. Our model describes, on a given platform, the evolution of attacks according to theirs hours. Afterward, we show the most attacked services by the studies of attacks on the various ports. It is advisable to note that this article was elaborated within the framework of the research projects on honeyspots within the LABTIC (Laboratory of Information Technologies and Communication).
Abstract: Intrusion Detection System is significant in network
security. It detects and identifies intrusion behavior or intrusion
attempts in a computer system by monitoring and analyzing the
network packets in real time. In the recent year, intelligent algorithms
applied in the intrusion detection system (IDS) have been an
increasing concern with the rapid growth of the network security.
IDS data deals with a huge amount of data which contains irrelevant
and redundant features causing slow training and testing process,
higher resource consumption as well as poor detection rate. Since the
amount of audit data that an IDS needs to examine is very large even
for a small network, classification by hand is impossible. Hence, the
primary objective of this review is to review the techniques prior to
classification process suit to IDS data.
Abstract: Performance of a limited Round-Robin (RR) rule is
studied in order to clarify the characteristics of a realistic sharing
model of a processor. Under the limited RR rule, the processor
allocates to each request a fixed amount of time, called a quantum, in a
fixed order. The sum of the requests being allocated these quanta is
kept below a fixed value. Arriving requests that cannot be allocated
quanta because of such a restriction are queued or rejected. Practical
performance measures, such as the relationship between the mean
sojourn time, the mean number of requests, or the loss probability and
the quantum size are evaluated via simulation. In the evaluation, the
requested service time of an arriving request is converted into a
quantum number. One of these quanta is included in an RR cycle,
which means a series of quanta allocated to each request in a fixed
order. The service time of the arriving request can be evaluated using
the number of RR cycles required to complete the service, the number
of requests receiving service, and the quantum size. Then an increase
or decrease in the number of quanta that are necessary before service is
completed is reevaluated at the arrival or departure of other requests.
Tracking these events and calculations enables us to analyze the
performance of our limited RR rule. In particular, we obtain the most
suitable quantum size, which minimizes the mean sojourn time, for the
case in which the switching time for each quantum is considered.
Abstract: Robot manipulators are highly coupled nonlinear
systems, therefore real system and mathematical model of dynamics
used for control system design are not same. Hence, fine-tuning of
controller is always needed. For better tuning fast simulation speed
is desired. Since, Matlab incorporates LAPACK to increase the speed
and complexity of matrix computation, dynamics, forward and
inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in
such a way that all operations are matrix based which give very less
simulation time. This paper compares PID parameter tuning using
Genetic Algorithm, Simulated Annealing, Generalized Pattern Search
(GPS) and Hybrid Search techniques. Controller performances for all
these methods are compared in terms of joint space ITSE and
cartesian space ISE for tracking circular and butterfly trajectories.
Disturbance signal is added to check robustness of controller. GAGPS
hybrid search technique is showing best results for tuning PID
controller parameters in terms of ITSE and robustness.
Abstract: Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.
Abstract: The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.
Abstract: Trace element speciation of an integrated soil
amendment matrix was studied with a modified BCR sequential
extraction procedure. The analysis included pseudo-total
concentration determinations according to USEPA 3051A and
relevant physicochemical properties by standardized methods. Based
on the results, the soil amendment matrix possessed neutralization
capacity comparable to commercial fertilizers. Additionally, the
pseudo-total concentrations of all trace elements included in the
Finnish regulation for agricultural fertilizers were lower than the
respective statutory limit values. According to chemical speciation,
the lability of trace elements increased in the following order: Hg <
Cr < Co < Cu < As < Zn < Ni < Pb < Cd < V < Mo < Ba. The
validity of the BCR approach as a tool for chemical speciation was
confirmed by the additional acid digestion phase. Recovery of trace
elements during the procedure assured the validity of the approach
and indicated good quality of the analytical work.
Abstract: The induction hardening machines are utilized in
the industries which modify machine parts and tools needed to
achieve high ware resistance. This paper describes the model of
induction heating process design of inverter circuit and the results
of induction surface hardening of heating coil. In the design of
heating coil, the shape and the turn numbers of the coil are very
important design factors because they decide the overall operating
performance of induction heater including resonant frequency, Q
factor, efficiency and power factor. The performance will be tested
by experiments in some cases high frequency induction hardening
machine.
Abstract: This paper presents the development of a Bayesian
belief network classifier for prediction of graft status and survival
period in renal transplantation using the patient profile information
prior to the transplantation. The objective was to explore feasibility
of developing a decision making tool for identifying the most suitable
recipient among the candidate pool members. The dataset was
compiled from the University of Toledo Medical Center Hospital
patients as reported to the United Network Organ Sharing, and had
1228 patient records for the period covering 1987 through 2009. The
Bayes net classifiers were developed using the Weka machine
learning software workbench. Two separate classifiers were induced
from the data set, one to predict the status of the graft as either failed
or living, and a second classifier to predict the graft survival period.
The classifier for graft status prediction performed very well with a
prediction accuracy of 97.8% and true positive values of 0.967 and
0.988 for the living and failed classes, respectively. The second
classifier to predict the graft survival period yielded a prediction
accuracy of 68.2% and a true positive rate of 0.85 for the class
representing those instances with kidneys failing during the first year
following transplantation. Simulation results indicated that it is
feasible to develop a successful Bayesian belief network classifier for
prediction of graft status, but not the graft survival period, using the
information in UNOS database.
Abstract: Bio-demographic diversity which refers to age and gender of members in a team, has been frequently identified to influence team innovation directly. As the theories expanded, biodemographic diversity was suggested to influence team innovation via psychosocial trait and interaction process. This study examines those suggestions, in which psychosocial trait and interaction process were operationalized as 'participation safety climate' and 'team reflexivity' respectively. The role of team reflexivity as a mediator to participation safety climate and team innovation was also assessed. Due to a small number of teams involved in the study, data were analyzed by using a PLS-graph. While the results show only gender is significantly related to the participation safety climate, which in turn influences team reflexivity and team innovation, there is no statistical evidence that team reflexivity mediates the impact of participation safety climate on team innovation.
Abstract: Different types of Islamic debts have been
increasingly utilized as preferred means of debt funding by
Malaysian private firms in recent years. This study examines the
impact of Islamic debts announcement on private firms- stock
returns. Our sample includes forty five listed companies on Bursa
Malaysia involved in issuing of Islamic debts during 2005 to 2008.
The abnormal returns and cumulative average abnormal returns are
calculated and tested using standard event study methodology. The
results show that a significant, negative abnormal return occurs one
day before announcement date. This negative abnormal return is
representing market participant-s adverse attitude toward Islamic
private debt announcement during the research period.
Abstract: In this paper, a system level behavioural model for RF
power amplifier, which exhibits memory effects, and based on multibranch
system is proposed. When higher order terms are included,
the memory polynomial model (MPM) exhibits numerical
instabilities. A set of memory orthogonal polynomial model
(OMPM) is introduced to alleviate the numerical instability problem
associated to MPM model. A data scaling and centring algorithm was
applied to improve the power amplifier modeling accuracy.
Simulation results prove that the numerical instability can be greatly
reduced, as well as the model precision improved with nonlinear
model.
Abstract: Populations of wild boar present in semi-arid of central Iran. We studied features influencing bed site selection by this species in semi-arid central steppe of Iran. Habitat features of the detected bed site were compared with randomly selected by quantifying number of habitat variables in semi- arid area in Iran. The results revealed that the most important influencing factors in bed site selection were vegetation cover, number of Artemisia sieberi, percentage cover and height of Acer cinerascens, percentage cover and height of Amygdalus scoparia. This is the first ecological study of the wild boar in a protected area of the semi desert biome of Iran. Sustainability of wild boar populations in this area dependent to shrubs of Amygdalus scoparia and Acer cinerascens for thermal and camouflage cover.